One of the best things about taking part in Marketo User Groups (MUGs) is that you get to hear from people that have “seen it, done it, and been there”. I had the opportunity to lead a panel discussion at the San Francisco MUG on the topic, Taking Out the Garbage: Real Life Experiences in Cleaning Up Your Data, where I was joined by Priya Malik of AppDynamics, Mitch Janning of Quantcast, Jake Dennison of Loggly, and Boris Butakov from Cord Blood Registry. All of the panelists were seasoned marketers with extensive marketing automation experience. They came from a wide range of industries and their Marketo instances ranged in size from 150,000 records to over 10 million.
What was interesting was that the panelists faced so many of the same issues. I only really had time to ask the panel a single question, “What are the biggest challenges you’ve faced with marketing automation when it comes to your data?” Everyone had a lot to say.
In this blog, I’ll cover the big issues with marketing data that our panel mentioned and their takeaways:
Working Productively With Sales Ops
A lot of panelists mentioned how difficult it can be when you own the data in your marketing automation data solution and someone in sales operations is responsible for what’s in salesforce.com, but there’s bi-directional integration between the two systems. The consensus was that regular meetings between marketing operations and sales operations are critical in order to be successful. To help ensure that things go smoothly, Mitch Janning suggested creating a document to spell out which organization is responsible for what at the field level and also to spell out from a business process standpoint when the handoff takes place from marketing to sales. To improve your process, use basic data governance templates you can use for Salesforce and Marketo fields.
Need help with creating a marketing and sales partnership? Check out this blog.
Working With 3rd Party Data
Many of the panelists mentioned some of the challenges of working with data providers that fell short of their claims to be able to clean and enrich their data. One panelist mentioned a match rate of only 21% between his records and a well-known data provider, so he wasn’t successful in being able to segment his leads by industry or department. Another mentioned a match rate of only 33%. One particularly interesting point raised by a panelist was his recommendation to ask your data provider about how to transform your data to match what the data provider needs to optimize results and how to best send that data. One of the panelists’ company was able to raise their match rate from 7% to 21% by doing that. Some on the panel suggested that having multiple data providers on board was the right approach to help with filling the gaps in your data.
To learn how to work more efficiently with your third-party data, check out this blog.
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